Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins

BACKGROUND

Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features.

METHODS

In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models.

RESULTS

The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation.

CONCLUSIONS

The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

Multifaceted role of drugs: a potential weapon to outsmart Mycobacterium tuberculosis resistance by targeting its essential ThyX

Tuberculosis (TB) is one of the prominent cause of deaths across the world and multidrug-resistant and extensively drug-resistant TB continues to pose challenges for clinicians and public health centers. The risk of death is extremely high in individuals who have compromised immune systems, HIV infection, or diabetes. Research institutes and pharmaceutical companies have been working on repurposing existing drugs as effective therapeutic options against TB. The identification of suitable drugs with multi-target affinity profiles is a widely accepted way to combat the development of resistance. Flavin-dependent thymidylate synthase (FDTS), known as ThyX, is in the class of methyltransferases and is a possible target in the discovery of novel anti-TB drugs. In this study, we aimed to repurpose existing drugs approved by Food and Drug Administration (FDA) that could be used in the treatment of TB. An integrated screening was performed based on computational procedures: high-throughput molecular docking techniques, followed by molecular dynamics simulations of the target enzyme, ThyX. After performing in silico screening using a library of 3,967 FDA-approved drugs, the two highest-scoring drugs, Carglumic acid and Mesalazine, were selected as potential candidates that could be repurposed to treat TB.Communicated by Ramaswamy H. Sarma.

Inhibitory mechanism of an antifungal drug, caspofungin against amyloid β peptide aggregation: Repurposing via neuroinformatics and an experimental approach

The multifactorial neurological condition called Alzheimer's disease (AD) primarily affects elderly individuals. Despite the calamitous consequences of AD, curative strategies for a regimen to apply remain inadequate as several factors contribute to AD etiology. Drug repurposing is an advance strategy prior to drug discovery as various effective drugs perform through alteration of multiple targets, and the present "poly-pharmacology" can be a curative approach to complex disorders. AD's multifactorial behavior actively encourages the hypothesis for a drug design approach focused on drug repurposing. In this study, we discovered that an antifungal drug, Caspofungin (CAS) is a potent Aβ aggregation inhibitor that displays significantly reduced toxicity associated with AD. Drug reprofiling and REMD simulations demonstrated that CAS interacts with the β-sheet section, known as Aβ amyloid fibrils hotspot. CAS leads to destabilization of β-sheet and, conclusively, in its devaluation. Later, in vitro experiments were acquired in which the fibrillar volume was reduced for CAS-treated Aβ peptide. For the first time ever, this study has determined an antifungal agent as the Aβ amyloid aggregation's potent inhibitor. Several efficient sequence-reliant potent inhibitors can be developed in future against the amyloid aggregation for different amyloid peptide by the processing and conformational optimization of CAS.

A systematic review and meta-analysis to evaluate the clinical outcomes in COVID-19 patients on angiotensin-converting enzyme inhibitors or angiotensin receptor blockers

INTRODUCTION

Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) share their target receptor site with the SARS-CoV-2 virus, that may cause ACE2 receptor up-regulation which raised concerns regarding ACEI and ARB use in COVID-19 patients. However, many medical professional societies recommended their continued use given the paucity of clinical evidence, but there is a need for an updated systematic review and meta-analysis of the latest clinical studies.

METHODS AND RESULTS

A search was conducted on PubMed, Google Scholar, EMBASE, and various preprint servers for studies comparing clinical outcomes and mortality in COVID-19 patients on ACEIs and/or ARBs, and a meta-analysis was performed. A total of 16 studies were included for the review and meta-analysis. There were conflicting findings reported in the rates of severity and mortality in several studies. In a pooled analysis of four studies, there was a statistically non-significant association of ACEI/ARB use with lower odds of developing severe disease vs. non-users [odds ratio (OR) = 0.81, 95% confidence interval (CI): 0.41-1.58, I2=50.52, P-value = 0.53). In a pooled analysis of six studies, there was a statistically non-significant association of ACEI/ARB use with lower odds of mortality as compared with non-users (OR = 0.86, 95% CI = 0.53-1.41, I2 = 79.12, P-value = 0.55).

CONCLUSION

It is concluded that ACEIs and ARBs should be continued in COVID-19 patients, reinforcing the recommendations made by several medical societies. Additionally, the individual patient factors such as ACE2 polymorphisms which might confer higher risk of adverse outcomes need to be evaluated further.

The polyphenolic phytoalexin polydatin inhibits amyloid aggregation of recombinant human prion protein

Prion diseases involve misfolded and highly infectious aggregates of prion protein (PrP^Sc) which forms amyloid plaques leading to fatal neurodegeneration. The absence of clinically proven therapeutics makes the discovery of effective remedial interventions a prime concern. Herein, we report novel prion intervention by the polyphenolic phytoalexin, polydatin which binds with moderate affinity to the recombinant protease resistant core of human prion protein, encompassing the sequence 90–231 (rPrP^res) and inhibits its conversion into the highly neurotoxic forms. An extensive evaluation using biophysical techniques revealed that polydatin incubated rPrP^res samples generate off-pathway oligomers having reduced cross-β sheet signature, and relatively smaller in size than the native rPrP^res oligomers. The detailed structural analysis using molecular dynamics simulations elucidated the induction of antagonistic mobilities in the β2–α2 loop, α3 helix and the N-terminal amyloidogenic region of prions. This study puts forward novel prion fibrillogenesis inhibitory potential of polydatin, specifically by stabilizing the N-terminal amyloidogenic region. Collectively our results affirm the importance of polydatin in crippling the prion pathogenesis and may serve as a structural scaffold for designing novel therapeutic agents targeting amyloidogenic transition in prions.

Polydatin is found to be a pharmacologically-significant scaffold that can bind to the rPrP^res repertoire and inhibit its conversion to the highly infectious and neurotoxic PrP^Sc-like form, thus acting like a promising anti-prion drug lead.

A Double-Edged Sword: The Anti-Cancer Effects of Emodin by Inhibiting the Redox-Protective Protein MTH1 and Augmenting ROS in NSCLC

Background: Reactive oxygen species (ROS), playing a two-fold role in tumorigenesis, are responsible for tumor formation and progression through the induction of genome instability and pro-oncogenic signaling. The same ROS is toxic to cancer cells at higher levels, oxidizing free nucleotide precursors (dNTPs) as well as damaging DNA leading to cell senescence. Research has highlighted the tumor cell-specific expression of a redox-protective phosphatase, MutT homolog 1 (MTH1), that performs the enzymatic conversion of oxidized nucleotides (like 8-oxo-dGTP) to their corresponding monophosphates, up-regulated in numerous cancers, circumventing their misincorporation into the genomic DNA and preventing damage and cell death. Methods: To identify novel natural small molecular inhibitors of MTH1 to be used as cancer therapeutic agents, molecular screening for MTH1 active site binders was performed from natural small molecular libraries. Emodin was identified as a lead compound for MTH1 active site functional inhibition and its action on MTH1 inhibition was validated on non-small cell lung cancer cellular models (NSCLC). Results: Our study provides strong evidence that emodin mediated MTH1 inhibition impaired NSCLC cell growth, inducing senescence. Emodin treatment enhanced the cellular ROS burdens, on one hand, damaged dNTP pools and inhibited MTH1 function on the other. Our work on emodin indicates that ROS is the key driver of cancer cell-specific increased DNA damage and apoptosis upon MTH1 inhibition. Consequently, we observed a time-dependent increase in NSCL cancer cell susceptibility to oxidative stress with emodin treatment. Conclusions: Based on our data, the anti-cancer effects of emodin as an MTH1 inhibitor have clinical potential as a single agent capable of functioning as a ROS inducer and simultaneous blocker of dNTP pool sanitation in the treatment of NSCL cancers. Collectively, our results have identified for the first time that the potential molecular mechanism of emodin function, increasing DNA damage and apoptosis in cancer cells, is via MTH1 inhibition.

Chondromyxoid Fibroma of the Temporal Bone: Case Report and Literature Review

Chondromyxoid fibroma (CMF) is a rare, benign, cartilaginous bone tumor that commonly affects the metaphysis of the lower-extremity long bones in young adults. Involvement of the craniofacial bones, especially the temporal bone, is exceedingly rare. We report a case of a 64-year-old man who presented with a left ear mass, but on subsequent imaging was found to have a more extensive mass centered in the temporal bone. Initial biopsy raised the concern for a low-grade chondrosarcoma. However, following surgical resection, a diagnosis of CMF was rendered. The clinical findings, radiographic features, histology, and differential diagnoses are discussed.

Dual inhibition of SARS-CoV-2 spike and main protease through a repurposed drug, rutin

The global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to alarming numbers of fatalities across the world. So far the researchers worldwide have not been able to discover a breakthrough in the form of a potent drug or an effective vaccine. Therefore, it is imperative to discover drugs to curb the ongoing menace. In silico approaches using FDA approved drugs can expedite the drug discovery process by providing leads that can be pursued. In this report, two drug targets, namely the spike protein and main protease, belonging to structural and non-structural class of proteins respectively, were utilized to carry out drug repurposing based screening. The exposed nature of the spike protein on the viral surface along with its instrumental role in host infection and the involvement of main protease in processing of polyproteins along with no human homologue make these proteins attractive drug targets. Interestingly, the screening identified a common high efficiency binding molecule named rutin. Further, molecular dynamics simulations in explicit solvent affirmed the stable and sturdy binding of rutin with these proteins. The decreased R_g value (4 nm for spike-rutin and 2.23 nm for main protease-rutin) and stagnant SASA analysis (485 nm/S²/N in spike-rutin and 152 nm/S2/N in main protease-rutin) for protein surface and its orientation in the exposed and buried regions suggests a strong binding interaction of the drug. Further, cluster analysis and secondary structure analysis of complex trajectories validated the conformational changes due to binding of rutin.

Multiple epitope-based vaccine prediction against SARS-CoV-2 spike glycoprotein

The global emergence of novel coronavirus disease and its rapid global expansion over a short span of time require effective countermeasures to combat it. Development of a specific vaccine can induce an optimal antibody response, thus providing immunity against it. Our study proposes a detailed and comprehensive immunoinformatic approach that can be applied to the currently available coronavirus protein data in the online server for vaccine candidate development. We have identified the receptor binding domain (RBD) of structural spike protein (S1) as a potential target for immunity against COVID- 19 infection. Epitope prediction illustrated cytotoxic T-cell epitopes, helper T-cell epitopes, and B-cell epitopes associated with the target protein. These were joined through specific linkers along with adjuvant beta-defensin located at the N-terminal to create a multi epitope subunit vaccine (MESV). The specificity in the binding of the devised vaccine candidate to the TLR-3 immune cell receptor was evaluated via molecular docking interaction studies. Good docking score combined with robust interactions in the binding cavity certified the stringency of the engineered vaccine. Molecular dynamics simulation data showed minimal variation of the root-mean square deviations (RMSDs) and root-mean-square fluctuations (RMSFs) which confirmed the interaction stability. These results obtained from various in-silico experiments indicate the potency of this vaccine candidate as a probable therapeutic agent against COVID-19. Vaccination strategies targeting conserved epitope-based immune response would be beneficial in providing cross protection across beta-coronaviruses, and such vaccines would be resistant to the ever-evolving viruses.Communicated by Ramaswamy H. Sarma.

Maslinic acid differentially exploits the MAPK pathway in estrogen-positive and triple-negative breast cancer to induce mitochondrion-mediated, caspase-independent apoptosis

Breast cancer accounts for 1.4 million new cases every year. Triple-negative breast cancer (TNBC) is one the leading cause of mortality in developing countries and is associated with early age onset (under 40 years old). Chemotherapy has a poor success rate in patients with TNBC as compared to other types of breast cancers. It is due to the lack of expression of three validated molecular markers for breast cancer, the estrogen and progesterone receptors, and the amplification of HER-2/Neu. Therefore, a clear need exists for a greater understanding of TNBC at all levels and for the development of better therapies. We have studied the anti-tumor effects of a potential drug, maslinic acid, which can be extracted from olive oil industry waste. This natural product showed inhibitory effect at concentrations ranging from 30 to 50 µM within 24 h. It exhibited divergent effects in cell cycle progression for the MCF7 (estrogen positive) cell line when compared with TNBCs like MDA-MB-231 and MDA-MB-468. Also, maslinic acid treatment altered the mitochondrial membrane electrochemical potential and the reactive oxygen species (ROS) levels to cause a caspase-independent programmed cell death. In silico approaches and immunoblotting suggested the involvement of the MAPK pathway explaining the variability in cell cycle progression along with the apoptotic cell death caused by maslinic acid.

Author Correction: Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Antitussive noscapine and antiviral drug conjugates as arsenal against COVID-19: a comprehensive chemoinformatics analysis

Coronavirus pandemic has caused a vast number of deaths worldwide. Thus creating an urgent need to develop effective counteragents against novel coronavirus disease (COVID-19). Many antiviral drugs have been repurposed for treatment but implicated minimal recovery, which further advanced the need for clearer insights and innovation to derive effective therapeutics. Strategically, Noscapine, an approved antitussive drug with positive effects on lung linings may show favorable outcomes synergistically with antiviral drugs in trials. Hence, we have theoretically examined the combinatorial drug therapy by culminating the existing experimental results with in silico analyses. We employed the antitussive noscapine in conjugation with antiviral drugs (Chloroquine, Umifenovir, Hydroxychloroquine, Favlplravir and Galidesivir). We found that Noscapine-Hydroxychloroquine (Nos-Hcq) conjugate has strong binding affinity for the main protease (Mpro) of SARS-CoV-2, which performs key biological function in virus infection and progression. Nos-Hcq was analyzed through molecular dynamics simulation. The MD simulation for 100 ns affirmed the stable binding of conjugation unprecedentedly through RMSD and radius of gyration plots along with critical reaction coordinate binding free energy profile. Also, dynamical residue cross-correlation map with principal component analysis depicted the stable binding of Nos-Hcq conjugate to Mpro domains with optimal secondary structure statistics of complex dynamics. Also, we reveal the drugs with stable binding to major domains of Mpro can significantly improve the work profile of reaction coordinates, drug accession and inhibitory regulation of Mpro. The designed combinatorial therapy paves way for further prioritized in vitro and in vivo investigations for drug with robust binding against Mpro of SARS-CoV-2.

Protective Effects of a Neurohypophyseal Hormone Analogue on Prion Aggregation, Cellular Internalization, and Toxicity

Herein, we report novel neuroprotective activity of the neurohypophyseal hormone analogue desmopressin (DDAVP) against toxic conformations of human prion protein. Systematic analysis using biophysical techniques in conjunction with surface plasmon resonance, high-end microscopy, conformational antibodies, and cell-based assays demonstrated DDAVP's specific binding and potent antiaggregating effects on prion protein (rPrP^res). In addition to subjugating conformational conversion of rPrP^res into oligomeric forms, DDAVP also exhibits potent fibril modulatory effects. It eventually ameliorated neuronal toxicity of rPrP^res oligomers by significantly reducing their cellular internalization. Molecular dynamics simulations showed that DDAVP prevents β-sheet transitions in the N-terminal amyloidogenic region of prion and induces antagonistic mobilities in its α2-α3 and β2-α2 loop regions. Collectively, our data proposes DDAVP as a new structural motif for rational drug discovery against prion diseases.

EUS-directed transgastric endoscopic retrograde cholangiopancreatography versus laparoscopic-assisted ERCP versus deep enteroscopy-assisted ERCP for patients with RYGB

Background and study aims  Endoscopic ultrasound-directed transgastric endoscopic retrograde cholangiopancreatography (ERCP) (EDGE) is a novel technique for managing pancreaticobiliary diseases in patients with a history of Roux-en-Y Gastric Bypass (RYGB). It has shown to have high technical success rates and fewer adverse events as compared to laparoscopic-assisted ERCP (LA-ERCP). We compared the technical success and clinical outcomes of EDGE vs. LA-ERCP vs. E-ERCP. Patients and methods  A retrospective chart review was performed for 56 patients, of whom 18 underwent LA-ERCP, 12 underwent E-ERCP, and 26 had EDGE, and a comparison of technical success and complication rates was done. Results  Baseline demographic characteristics of patients undergoing these procedures, including age and gender, were comparable. The technical success rate for patients in the EDGE group were 100 % (n = 26), compared with 94 % (n = 17) and 75 % (n = 9) in the LA-ERCP and E-ERCP groups ( P  = 0.02). In the EDGE group, 8 % of patients (n = 2) had bleeding, and 4 % of patients (n = 1) had lumen-apposing metal stent migration occur during the procedure. In the LA-ERCP group 6 % (n = 1) of patient had bleeding, 6 % (n = 1) post-ERCP pancreatitis and 6 % (n = 1) were diagnosed with an intra-abdominal infection post-procedure. Time to complete the EDGE procedure was significantly shorter at 79 ± 31 mins, compared with 158 ± 50 mins for LA-ERCP and 102 ± 43 mins for E-ERCP ( P  < 0.001). Conclusion  EDGE is a novel procedure with short procedure times and an effective alternative to LA-ERCP and E-ERCP in management of pancreaticobiliary diseases in patients with a history of RYGB.

Risk of de-novo inflammatory bowel disease among obese patients treated with bariatric surgery or weight loss medications

BACKGROUND

An association between bariatric surgery and development of de-novo inflammatory bowel disease (IBD) has been observed.

AIM

To evaluate further the association among bariatric surgery, weight loss medications, obesity and new-onset IBD.

METHODS

Using Explorys, a population-based Health Insurance Portability and Accountability Act compliant database, we estimated the prevalence of de-novo IBD among patients treated with bariatric surgery (Roux-en-Y gastrojejunostomy, laparoscopic sleeve gastrectomy or gastric banding) (n = 60 870) or weight loss medications (orlistat, phentermine/topiramate, lorcaserin, bupropion/naltrexone and liraglutide) (n = 193 790) compared with obese controls (n = 5 021 210), between 1999 and 2018.

RESULTS

The prevalence of de-novo IBD was lower among obese patients exposed to bariatric surgery (7.72 per 1000 patients) or weight loss medications (7.22 per 1000 patients) compared with patients with persistent obesity not exposed to these interventions (11.66 per 1000 patients, P < 0.0001). The risk reduction for de-novo IBD was consistent across bariatric surgeries and weight loss medications with the exception of orlistat which was not associated with a reduction in risk for de-novo IBD compared with the persistent obese control cohort.

CONCLUSION

Obese patients undergoing treatment with bariatric surgery or weight loss medications are at a lower risk for developing de-novo IBD compared with persistently obese controls not exposed to these interventions. These data suggest that obesity and ineffective management of obesity are risk factors for de-novo IBD. Further research is needed to confirm these observations and understand potential mechanisms.

Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest number of deaths globally for any bacterial disease necessitating novel diagnosis and treatment strategies. High-throughput sequencing methods generate a large amount of data which could be exploited in determining multi-drug resistant (MDR-TB) associated mutations. The present work is a computational framework that uses artificial intelligence (AI) based machine learning (ML) approaches for predicting resistance in the genes rpoB, inhA, katG, pncA, gyrA and gyrB for the drugs rifampicin, isoniazid, pyrazinamide and fluoroquinolones. The single nucleotide variations were represented by several sequence and structural features that indicate the influence of mutations on the target protein coded by each gene. We used ML algorithms - naïve bayes, k nearest neighbor, support vector machine, and artificial neural network, to build the prediction models. The classification models had an average accuracy of 85% across all examined genes and were evaluated on an external unseen dataset to demonstrate their application. Further, molecular docking and molecular dynamics simulations were performed for wild type and predicted resistance causing mutant protein and anti-TB drug complexes to study their impact on the conformation of proteins to confirm the observed phenotype.

Long-range replica exchange molecular dynamics guided drug repurposing against tyrosine kinase PtkA of Mycobacterium tuberculosis

Tuberculosis (TB) is a leading cause of death worldwide and its impact has intensified due to the emergence of multi drug-resistant (MDR) and extensively drug-resistant (XDR) TB strains. Protein phosphorylation plays a vital role in the virulence of Mycobacterium tuberculosis (M.tb) mediated by protein kinases. Protein tyrosine phosphatase A (MptpA) undergoes phosphorylation by a unique tyrosine-specific kinase, protein tyrosine kinase A (PtkA), identified in the M.tb genome. PtkA phosphorylates PtpA on the tyrosine residues at positions 128 and 129, thereby increasing PtpA activity and promoting pathogenicity of MptpA. In the present study, we performed an extensive investigation of the conformational behavior of the intrinsically disordered domain (IDD) of PtkA using replica exchange molecular dynamics simulations. Long-term molecular dynamics (MD) simulations were performed to elucidate the role of IDD on the catalytic activity of kinase core domain (KCD) of PtkA. This was followed by identification of the probable inhibitors of PtkA using drug repurposing to block the PtpA-PtkA interaction. The inhibitory role of IDD on KCD has already been established; however, various analyses conducted in the present study showed that IDD_PtkA had a greater inhibitory effect on the catalytic activity of KCD_PtkA in the presence of the drugs esculin and inosine pranobex. The binding of drugs to PtkA resulted in formation of stable complexes, indicating that these two drugs are potentially useful as inhibitors of M.tb.

Self-reported Morisky Eight-item Medication Adherence Scale for Statins Concords with the Pill Count Method and Correlates with Serum Lipid Profile Parameters and Serum HMGCoA Reductase Levels

Background It is imperative that non-compliance with statins be identified and addressed to maximize their clinical benefits. Patient self-reporting methods are convenient to apply in clinical practice but need to be validated. Objective We studied the concordance of a patient self-report method, Morisky eight-item medication adherence scale (MMAS)), with the pill count method in measuring adherence with statins and their correlation with extended lipid profile parameters and serum hydroxyl-methylglutaryl coenzyme A reductase (HMGCoA-R) enzyme levels. Methods MMAS and the pill count method were used to measure the adherence with statins in patients on statins for any duration. Patients were subjected to an estimation of extended lipid profile and serum HMGCoA-R levels at the end of three months follow-up. Results Out of a total of 200 patients included in the study, 117 patients had a low adherence (score less than 6 on MMAS) whereas 65 and 18 patients had medium (score 6 or 7) and high adherence (score of 8), respectively. The majority of patients who had low adherence to statins by MMAS were nonadherent by the pill count method yielding a concordance of 96.5%. Medium or high adherence to statins by the MMAS method had a concordance of 89.1% with the pill count method. The levels of total cholesterol, low-density lipoprotein-cholesterol, apolipoprotein B, and HMGCoA-R were negatively correlated with compliance measured by pill count and MMAS in a statistically significant way and with similar correlation coefficients. HMGCoA-R levels demonstrated a plateau phenomenon, with levels being 9-10 ng/ml when compliance with statin therapy was greater than 60% by pill count and greater than 6 on the Morisky scale. Conclusion In conclusion, MMAS and the pill count method showed concordance in measuring adherence to statins. These methods need to be explored further for their interchangeability as surrogates for biomarker levels.

Electronic structure of iron dinitrogen complex [(TPB)FeN2]2−/1−/0: correlation to Mössbauer parameters

Low-valent species of iron are key intermediates in many important biological processes such as the nitrogenase enzymatic catalytic reaction. These species play a major role in activating highly stable N₂ molecules. Thus, there is a clear need to establish the factors which are responsible for the reactivity of the metal–dinitrogen moiety. In this regard, we have investigated the electronic structure of low-valent iron (2−/1−/0) in a [(TPB)FeN₂]^2−/1−/0 complex using density functional theory (DFT). The variation in the oxidation states of iron in the nitrogenase enzyme cycle is associated with the flexibility of Fe→B bonding. Therefore, the flexibility of Fe→B bonding acts as an electron source that sustains the formation of various oxidation states, which is necessary for the key species in dinitrogen activation. AIM calculations are also performed to understand the strength of Fe→B and Fe–N₂ bonds. A detailed interpretation of the contributions to the isomer shift (IS) and quadrupole splitting (ΔE_Q) are discussed. The major contribution to IS comes mainly from the 3s-contribution, which differs depending on the d orbital population due to different shielding. The valence shell contribution also comes from the 4s-orbital. The Fe–N₂ bond distance has a great influence on the Mössbauer parameters, which are associated with the radial distribution, i.e. the shape of the 4s-orbital and the charge density at the nucleus. A linear relationship between IS with Fe–N₂ and ΔE_Q with Fe–N₂ is observed.

We use density functional theory studies to explore the electronic structure, bonding and spectroscopic analysis of a low-valent iron (2−/1−/0) complex [(TPB)FeN₂]^2−/1−/0 and reveled the factor which affects the reactivity of the metal–dinitrogen moiety.

Bleomycin modulates amyloid aggregation in β-amyloid and hIAPP

Aberrant misfolding and amyloid aggregation, which result in amyloid fibrils, are frequent and critical pathological incidents in various neurodegenerative disorders. Multiple drugs or inhibitors have been investigated to avert amyloid aggregation in individual peptides, exhibiting sequence-dependent inhibition mechanisms. Establishing or inventing inhibitors capable of preventing amyloid aggregation in a wide variety of amyloid peptides is quite a daunting task. Bleomycin (BLM), a complex glycopeptide, has been widely used as an antibiotic and antitumor drug due to its ability to inhibit DNA metabolism, and as an antineoplastic, especially for solid tumors. In this study, we investigated the dual inhibitory effects of BLM on Aβ aggregation, associated with Alzheimer's disease and hIAPP, which is linked to type 2 diabetes, using both computational and experimental techniques. Combined results from drug repurposing and replica exchange molecular dynamics simulations demonstrate that BLM binds to the β-sheet region considered a hotspot for amyloid fibrils of Aβ and hIAPP. BLM was also found to be involved in β-sheet destabilization and, ultimately, in its reduction. Further, experimental validation through in vitro amyloid aggregation assays was obtained wherein the fibrillar load was decreased for the BLM-treated Aβ and hIAPP peptides in comparison to controls. For the first time, this study shows that BLM is a dual inhibitor of Aβ and hIAPP amyloid aggregation. In the future, the conformational optimization and processing of BLM may help develop various efficient sequence-dependent inhibitors against amyloid aggregation in various amyloid peptides.

Bleomycin acts as a dual inhibitor against both amyloid β and human islet amyloid polypeptide by binding to the β-sheet grooves considered as the amyloids hotspot.

Ameliorating amyloid aggregation through osmolytes as a probable therapeutic molecule against Alzheimer's disease and type 2 diabetes

Large numbers of neurological and metabolic disorders occurring in humans are induced by the aberrant growth of aggregated or misfolded proteins.

Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder in which the death of brain cells takes place leading to loss of memory and decreased cognitive ability. AD is a leading cause of death worldwide and is progressive in nature with symptoms worsening over time. Machine learning–based computational predictive models based on 2D and 3D descriptors have been effective in identifying potential active compounds. However, the use of data from molecular dynamics (MD) trajectories for training machine learning models still needs to be explored. In the present study, descriptors have been extracted from the MD trajectories of caspase-8 ligand complexes to train models using artificial neural networks and random forest algorithms. Caspase-8 plays a key role in causing AD by cleaving amyloid precursor proteins during apoptosis leading to increased formation of the amyloid-beta peptide. A total of 43 ligands were docked using the glide module of Schrodinger software, and short MD simulations of 10 ns were performed for the calculation of MD descriptors. The MD descriptors were also combined with the 2D and 3D descriptors of chemical compounds, and individual descriptor based as well as combination models were generated. This study demonstrated that MD descriptors could be effectively used for the characterization of bioactive compounds along with lead prioritization and optimization.